Probabilistic Approach to Determine the Spatial Distribution of the Antecedent Moisture Conditions for Different Return Periods in the Atlántico Region, Colombia

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dc.contributor.authorSalgado-Cassiani, J.
dc.contributor.authorCoronado-Hernández, O.
dc.contributor.authorGatica, G.
dc.contributor.authorLinfati, R.
dc.contributor.authorCoronado-Hernández, J.
dc.date.accessioned2022-05-10T16:56:31Z
dc.date.available2022-05-10T16:56:31Z
dc.date.issued2022-04
dc.descriptionIndexación: Scopus.es
dc.description.abstractPrevious soil moisture conditions play an important role in the design of hydraulic structures because they are directly related to the runoff threshold associated with a return period. These represent one of the main determinants of the runoff response of a drainage basin. One of the main difficulties facing hydrologists in Colombia lies in the time spent gathering and analyzing information related to the selection of antecedent moisture conditions. In this study, complete records from 19 rainfall stations located in the Atlántico region, Colombia, were used to analyze the cumulative precipitation during the 5 days prior to the annual maximum daily precipitation associated with different return periods using the Gev, Gumbel, Pearson Type III and Log Pearson Type III probability distributions. Different interpolation methods (IDW, kriging and spline) were applied to evaluate the spatial distribution of the antecedent moisture conditions. The main contribution of this research is establishing, using a probabilistic approach, the behavior of antecedent moisture conditions in a particular region, which can be used by engineers and designers to plan water infrastructure. This probabilistic approach was applied to a case study of the Atlántico region, Colombia, where the spatial distribution of antecedent moisture conditions was calculated for several return periods. The results indicate that the better results were obtained with the IDW interpolation method, and the Pearson Type III and Gumbel distributions also showed the best fits based on the Akaike criterion.es
dc.description.urihttps://www.mdpi.com/2073-4441/14/8/1217
dc.identifier.citationWater (Switzerland), Volume 14, Issue 8, April-2 2022, Article number 1217es
dc.identifier.doi10.3390/w14081217
dc.identifier.issn2073-4441
dc.identifier.urihttps://repositorio.unab.cl/xmlui/handle/ria/22485
dc.language.isoenes
dc.publisherMDPIes
dc.rights.licenseAtribución 4.0 Internacional (CC BY 4.0)
dc.rights.urihttps://www.mdpi.com/openaccess
dc.subjectantecedent moisture conditiones
dc.subjectfrequency analysises
dc.subjectprecipitationes
dc.subjectreturn periodes
dc.subjectCatchmentses
dc.subjectInterpolationes
dc.subjectProbability distributionses
dc.subjectRunoffes
dc.subjectSoil moisturees
dc.titleProbabilistic Approach to Determine the Spatial Distribution of the Antecedent Moisture Conditions for Different Return Periods in the Atlántico Region, Colombiaes
dc.typeArtículoes
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